[FIXED] how to split dataframe if column value change value python

Issue

i want to split dataframe when value of flag column change to 1

df=pd.DataFrame({'A':[1,20,40,45,56,1,20,40,45,56],'flag':[3,2,4,1,1,3,3,1,1,1]})

Out[63]: 
    A  flag
0   1     3
1  20     2
2  40     4
3  45     1
4  56     1
5   1     3
6  20     3
7  40     1
8  45     1
9  56     1

desired out:

print(group_1)
    A  flag
0   1     3
1  20     2
2  40     4

print(group_2)
    A  flag
0   1     3
1  20     3

Solution

You can use groupby on the masked DataFrame, with groups starting on each 1:

mask = df['flag'].eq(1)
groups = [g for _,g in df[~mask].groupby(mask.cumsum())]

output:

groups[0]

    A  flag
0   1     3
1  20     2
2  40     4

groups[1]

    A  flag
5   1     3
6  20     3

Answered By - mozway